Automation index
How much of a Judge’s job can AI already do?
Sorting the file and a first order come earlier. Sentencing a person, looking them in the eye, and signing do not.
This percentage does not predict how many people will lose their jobs.
Task comparison
IS WORK OVER?
Judge
19%
AI can already do 19% of this job.
#506 / 633
View rankingJudge
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Read, index and summarise the case file.EstimateNo public source provides a precise figure. This is our estimate. | 20% | 38% | +7.6 |
Draft routine orders and procedural rulings.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 32% | +5.1 |
Hearing, examination and adversarial argument.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 12% | +2.2 |
Weigh evidence, credibility and context.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 10% | +1.8 |
Write and reason the judgment.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
Sign, own the decision and preside.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 6% | +0.7 |
| Total | 100% | 19% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- Read, index and summarise the case file
- Weigh evidence, credibility and context
- Write and reason the judgment
- Sign, own the decision and preside
- juez
- jueza
- judge
- magistrad
Sources for this job· O*NET 23-1023.00· ESCO/ISCO 2612
IS WORK OVER?
Data architect
28%
#83 / 633
View rankingData architect
Where the time goes
Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.
The time saving for each task is estimated separately.
| Task | Share | AI | Points |
|---|---|---|---|
Models, lineage and the catalogue.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Pipelines, quality and the data contract.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 40% | +6.4 |
The analyst who finds nothing and the mess.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Privacy, retention and the field you cannot keep.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
The business, shadow IT and not building another lake.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 14% | +2.5 |
That it gets used, and not letting raw data rot.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 12% | +1.9 |
| Total | 100% | 28% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- model data
- lineage
- data catalogue
- data contracts
- pipeline quality
- retention
- data lakes
- privacy
Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511